Service level agreement management framework for utility-oriented computing platforms

With the increasing popularity of utility-oriented computing where the resources are traded as services, efficient management of quality of service (QoS) has become increasingly significant to both service consumers and service providers. In the context of distributed multimedia content adaptation deployment on service-oriented computing, how to ensure the stringent QoS requirements of the content adaptation is a significant and immediate challenge. However, QoS guarantees in the distributed multimedia content adaptation deployment on service-oriented platform context have not been accorded the attention it deserves. In this paper, we address this problem. We formulate the SLA management for distributed multimedia content adaptation deployment on service-oriented computing as an integer programming problem. We propose an SLA management framework that enables the service provider to determine deliverable QoS before settling SLA with potential service consumers to optimize QoS guarantees. We analyzed the performance of the proposed strategy under various conditions in terms of the SLA success rate, rejection rate and impact of the resource data errors on potential violation of the agreed upon SLA. We also compared the proposed SLA management framework with a baseline approach in which the distributed multimedia content adaptation is deployed on a service-oriented platform without SLA consideration. The results of the experiments show that the proposed SLA management framework substantially outperforms the baseline approach confirming that SLA management is a core requirement for the deployment of distributed multimedia content adaptation on service-oriented systems.

Polyhedral results for the Cardinality Constrained Multi-cycle Problem (CCMcP) and the Cardinality Constrained Cycles and Chains Problem (CCCCP)

In recent years, there has been studies on the cardinality constrained multi-cycle problems on directed graphs, some of which considered chains co-existing on the same digraph whilst others did not. These studies were inspired by the optimal matching of kidneys known as the Kidney Exchange Problem (KEP). In a KEP, a vertex on the digraph represents a donor-patient pair who are related, though the kidney of the donor is incompatible to the patient. When there are multiple such incompatible pairs in the kidney exchange pool, the kidney of the donor of one incompatible pair may in fact be compatible to the patient of another incompatible pair. If Donor A’s kidney is suitable for Patient B, and vice versa, then there will be arcs in both directions between Vertex A to Vertex B. Such exchanges form a 2-cycle. There may also be cycles involving 3 or more vertices. As all exchanges in a kidney exchange cycle must take place simultaneously, (otherwise a donor can drop out from the program once his/her partner has received a kidney from another donor), due to logistic and human resource reasons, only a limited number of kidney exchanges can occur simultaneously, hence the cardinality of these cycles are constrained. In recent years, kidney exchange programs around the world have altruistic donors in the pool. A sequence of exchanges that starts from an altruistic donor forms a chain instead of a cycle. We therefore have two underlying combinatorial optimization problems: Cardinality Constrained Multi-cycle Problem (CCMcP) and the Cardinality Constrained Cycles and Chains Problem (CCCCP). The objective of the KEP is either to maximize the number of kidney matches, or to maximize a certain weighted function of kidney matches. In a CCMcP, a vertex can be in at most one cycle whereas in a CCCCP, a vertex can be part of (but in no more than) a cycle or a chain. The cardinality of the cycles are constrained in all studies. The cardinality of the chains, however, are considered unconstrained in some studies, constrained but larger than that of cycles, or the same as that of cycles in others. Although the CCMcP has some similarities to the ATSP- and VRP-family of problems, there is a major difference: strong subtour elimination constraints are mostly invalid for the CCMcP, as we do allow smaller subtours as long as they do not exceed the size limit. The CCCCP has its distinctive feature that allows chains as well as cycles on the same directed graph. Hence, both the CCMcP and the CCCCP are interesting and challenging combinatorial optimization problems in their own rights. Most existing studies focused on solution methodologies, and as far as we aware, there is no polyhedral studies so far. In this paper, we will study the polyhedral structure of the natural arc-based integer programming models of the CCMcP and the CCCCP, both containing exponentially many constraints. We do so to pave the way for studying strong valid cuts we have found that can be applied in a Lagrangean relaxation-based branch-and-bound framework where at each node of the branch-and-bound tree, we may be able to obtain a relaxation that can be solved in polynomial time, with strong valid cuts dualized into the objective function and the dual multipliers optimised by subgradient optimisation.

Intensive care unit discharge policies prior to treatment completion

In this study we explore a model to optimize the Intensive Care Unit (ICU) discharging decisions prior to service completion as a result of capacity-constrained situation under uncertainty. Discharging prior to service completion, which is called demand-driven discharge or premature discharging, increases the chance that a patient to be readmitted to the ICU in the near future. Since readmission imposes an additional load on ICUs, the cost of demand-driven discharge is pertained to the surge of readmission chance and the length of stay (LOS) in the ICU after readmission. Hence, the problem is how to select a current patient in the ICU for demand-driven discharge to accommodate a new critically ill patient. In essence, the problem is formulated as a stochastic dynamic programming model. However, even in the deterministic form i.e. knowing the arrival and treatment times in advance, solving the dynamic programming model is almost unaffordable for a sizable problem. This is illustrated by formulating the problem by an integer programming model. The uncertainties and difficulties in the problem are convincing reasons to use the optimization-simulation approach. Thus, using simulations, we evaluate various scenarios by considering Weibull distribution for the LOS. While it is known that selecting a patient with the lowest readmission risk is optimum under certain conditions and supposing a memory-less distribution for LOS; we remark that when LOS is non-memory-less, considering readmission risk and remaining LOS rather than just readmission risk leads to better results.

Achieving behaviour change: three generations of HIV/AIDS programming and jargon in Thailand

NGOs have played an important role worldwide in the fight to prevent the spread of HIV/AIDS through achieving behaviour change. NGOs have often been at the forefront of innovative changes, influencing government and international programming activities. This paper identifies and analyses the evolution of the HIV/AIDS programmes of one NGO in Thailand over a period of ten years. Three generations of programming are identified both through distinct approaches to this area of work and through the changing jargon used to describe the people the programmes are aimed at.

Evolutionary multiobjective optimization in engineering management: an empirical study on bridge deck rehabilitation

There exist multiple objectives in engineering management such as minimum cost and maximum service capacity. Although solution methods of multiobjective optimization problems have undergone continual development over the past several decades, the methods available to date are not particularly robust, and none of them performs well on the broad classes. Because genetic algorithms work with a population of points, they can capture a number of solutions simultaneously, and easily incorporate the concept of Pareto optimal set in their optimization process. In this paper, a genetic algorithm is modified to deal with the rehabilitation planning of bridge decks at a network level by minimizing the rehabilitation cost and deterioration degree simultaneously.

Evolutionary multiobjective optimization in engineering management: an empirical application in infrastructure systems

Generally multiple objectives exist in transportation infrastructure management, such as minimum cost and maximum service capacity. Although solution methoak of multiobjective optimization problems have undergone continual development over the part several decades, the methods available to date are not particularly robust, and none of them perform well on the broad classes. Because genetic algorithms work with apopulation ofpoints, they can capture a number of solutions simultaneously, and easily incorporate the concept of a Pareto optimal set in their optimization process. In this paper, a genetic algorithm is modified to deal with an empirical application for the rehabilitation planning of bridge decks, at a network level, by minimizing the rehabilitation cost and deterioration degree simultaneously.

Design guidelines for children programming in school environment

This paper describes design guidelines of a programming environment for children, aiming to lower the barriers for children to learn programming. Our model called GBuilder has been developed on the basis of guidelines, with the express purpose of enabling and empowering the students to develop their own learning programs in survival literacy within enjoyable and fun environment.

Polyhedral results and exact algorithms for the asymmetric travelling salesman problem with replenishment arcs

The asymmetric travelling salesman problem with replenishment arcs (RATSP), arising from work related to aircraft routing, is a generalisation of the well-known ATSP. In this paper, we introduce a polynomial size mixed-integer linear programming (MILP) formulation for the RATSP, and improve an existing exponential size ILP formulation of Zhu [The aircraft rotation problem, Ph.D. Thesis, Georgia Institute of Technology, Atlanta, 1994] by proposing two classes of stronger cuts. We present results that under certain conditions, these two classes of stronger cuts are facet-defining for the RATS polytope, and that ATSP facets can be lifted, to give RATSP facets. We implement our polyhedral findings and develop a Lagrangean relaxation (LR)-based branch-and-bound (BNB) algorithm for the RATSP, and compare this method with solving the polynomial size formulation using ILOG Cplex 9.0, using both randomly generated problems and aircraft routing problems. Finally we compare our methods with the existing method of Boland et al. [The asymmetric traveling salesman problem with replenishment arcs, European J. Oper. Res. 123 (2000) 408–427]. It turns out that both of our methods are much faster than that of Boland et al. [The asymmetric traveling salesman problem with replenishment arcs, European J. Oper. Res. 123 (2000) 408–427], and that the LR-based BNB method is more efficient for problems that resemble the aircraft rotation problems.

Implementation of novel methods of global and nonsmooth optimization : GANSO programming library

We discuss the implementation of a number of modern methods of global and nonsmooth continuous optimization, based on the ideas of Rubinov, in a programming library GANSO. GANSO implements the derivative-free bundle method, the extended cutting angle method, dynamical system-based optimization and their various combinations and heuristics. We outline the main ideas behind each method, and report on the interfacing with Matlab and Maple packages.

Opportunities and challenges with J2SE 5 for introductory programming teaching

The recent release of the Java version 5.0 "Tiger" introduces some significant language changes. For educators, some of these changes provide opportunities to improve teaching, while others pose additional problems that require awareness to avoid them. The authors have recently completed the inclusion of support for all new language features into a wellknown educational IDE for Java – BlueJ – and in the course of doing so evaluated each of them for usefulness in education, and developed pedagogic strategies to handle the inherent opportunities and challenges. This has formed the basis of the design of the features in BlueJ which support the language changes. In this paper, we describe the results of our evaluation, provide recommendations on treatment of the new features in introductory courses and discuss how BlueJ may be used to illustrate important aspects.

Programming your - objects (turtles, textboxes, sliders and buttons) in microworlds

This article outlines some new-object commands of Logo Microworlds and includes the use of buttons, sliders and programmable colours. The ability to assign object properties including font, colour and frames are discussed. As is assigning object-instructions and commands such as click on and clickoff, launch and cancel. Programming the turtle, making a new turtle, running simultaneous turtles, programming graphic colours and sliders as well as understanding dotimes are explored.

Introductory computer programming as a means for extending spatial and temporal understanding

Should computer programming be taught within schools of architecture?

Incorporating even low-level computer programming within architectural education curricula is a matter of debate but we have found it useful to do so for two reasons: as an introduction or at least a consolidation of the realm of descriptive geometry and in providing an environment for experimenting in morphological time-based change.

Mathematics and descriptive geometry formed a significant proportion of architectural education until the end of the 19th century. This proportion has declined in contemporary curricula, possibly at some cost for despite major advances in automated manufacture, Cartesian measurement is still the principal ‘language’ with which to describe building for construction purposes. When computer programming is used as a platform for instruction in logic and spatial representation, the waning interest in mathematics as a basis for spatial description can be readdressed using a left-field approach. Students gain insights into topology, Cartesian space and morphology through programmatic form finding, as opposed to through direct manipulation.

In this context, it matters to the architect-programmer how the program operates more than what it does. This paper describes an assignment where students are given a figurative conceptual space comprising the three Cartesian axes with a cube at its centre. Six Phileban solids mark the Cartesian axial limits to the space. Any point in this space represents a hybrid of one, two or three transformations from the central cube towards the various Phileban solids. Students are asked to predict the topological and morphological outcomes of the operations. Through programming, they become aware of morphogenesis and hybridisation. Here we articulate the hypothesis above and report on the outcome from a student group, whose work reveals wider learning opportunities for architecture students in computer programming than conventionally assumed.

History, memory, and the politics of programming : the video work of Richard Fung

Richard Fung, a Toronto-based video artist and cultural critic, was born in Trinidad in 1954, and attended school in Ireland before immigrating to Canada to study at the University of Toronto. Richard Fung has taught at the Ontario College of Art and Design, and has been a visiting professor in the Department of Media Study at the State University of New York in Buffalo. He is currently the coordinator of the Centre for Media and Culture in Education, Ontario Institute for Studies in Education, University of Toronto.